Extreme heat is a prolific weather-related killer in the United States as well as the rest of the world. Notable extreme heat events (EHE's) within the last two decades include a seven day period in Philadelphia, Pa., in July of 1993 accounting for 118 deaths and a less than seven day period Chicago, Ill., in July of 1995 accounting for 700 deaths. Outside of North America, France experienced an EHE in the summer of 2003 that accounted over tens of thousands of deaths. Thus, heat-related morbidity and mortality are among the primary health concerns expected to increase as a function of climate change.
There is significant disparity in the populations involved in heat-related morbidity/mortality. Generally, various social characteristics have been associated with urban disasters. Those sufferers of poverty, those with poor education, those designated by minority status, the very young, and the elderly are groups identified as disproportionally impacted by urban disasters. However, the distribution of vulnerability to EHEs among the various groups, as defined by the social characteristics listed above and various combinations of the same, is largely unknown. Furthermore, the interaction between the various social characteristics and EHEs is not simple, and is further exacerbated by built (urban) environments.
The urban heat island (UHI) effect, a function of the urban environment, is defined as the temperature differential between the contiguous rural area and its related urbanized space. The UHI effect likely serves to magnify the lethality of EHEs. The effect, however, is not a straight forward and simple magnification. The UHI effect is complex and dependent upon a number of factors. The UHI effect stems from the lack of vegetation, low thermal conductivity and/or high heat capacity materials used in the built environment, and the urban canyon-like geometry. UHIs are typically spatially heterogeneous, with differing levels of heat intensity occurring within a city (aka micro-UHIs). Vulnerable groups spatially coincident with these micro-UHIs are thought to be at an even greater increased risk of heat-related mortality.
The spatial analysis of vulnerability, linking social and built environment variables to EHEs within urban areas, is limited. Investigators have demonstrated that warmer and more socially disadvantaged areas are more prone to heat-related deaths. But investigators have undertaken no direct physical measure of temperature. Furthermore, there has been no adequate measure of heat load or of the socioeconomic disadvantages of a given neighborhood in relation to UHI's or EHE's.
Previous approaches utilizing the Human Thermal Comfort Index (HTCI) suffer from a similar problem. While indicating a strong positive spatial relationship between heat stress and the percentage of poverty and minority, these approaches suffer from using estimated UHIs as well as from a lack of a direct accounting for socioeconomic factors. In essence, previous approaches fail in as far as they does not provide a true or useful mechanism with which to predict where the greatest concentrations of mortality and morbidity will occur within an urban environment during an EHE.
Cities are facing ever greater financial constraints upon their abilities to respond to social and environmental harms. Additionally, it is expected that EHEs will likely increase both in duration and intensity as a result of climate transformation. Taken together, these elements indicate a scenario that underscores the need to further understand the phenomena of extreme heat, identify at-risk populations and mitigate effects and impacts upon those populations. Cities must be able to better predict where their EHE response mechanisms must be concentrated to most effectively combat the mortality and morbidity caused by future EHEs. The enhanced ability to delineate the risk of morbidity and mortality at finer scales within urban environments will enable better and more cost effective concentration of mitigation efforts and preventative measures yielding improved medical and preventative responses and superior post EHE recovery.
Thus there remains a need for an improved, spatially specific method to identify populations at risk from EHE's. The present novel technology addresses this need.